
import numpy as np
import physo

z = np.random.uniform(-10, 10, 50)
v = np.random.uniform(-10, 10, 50)
X = np.stack((z, v), axis=0)
y = 1.234*9.807*z + 1.234*v**2
# set 1


# set 1. Symbolic regression with default hyperparameters.
expression, logs = physo.SR(X, y,
                            X_units = [ [1, 0, 0] , [1, -1, 0] ],
                            y_units = [2, -2, 1],
                            fixed_consts       = [ 1.      ],
                            fixed_consts_units = [ [0,0,0] ],
                            free_consts_units  = [ [0, 0, 1] , [1, -2, 0] ],
)
# set 2 Hyperparameters configurations.
expression, logs = physo.SR(X, y,
                            X_units = [ [1, 0, 0] , [1, -1, 0] ],
                            y_units = [2, -2, 1],
                            fixed_consts       = [ 1.      ],
                            fixed_consts_units = [ [0,0,0] ],
                            free_consts_units  = [ [0, 0, 1] , [1, -2, 0] ],
                            run_config = physo.config.config1.config1
)
# set 3. Selectable symbolic operations.
expression, logs = physo.SR(X, y,
                            X_names = [ "z"       , "v"        ],
                            X_units = [ [1, 0, 0] , [1, -1, 0] ],
                            y_name  = "E",
                            y_units = [2, -2, 1],
                            fixed_consts       = [ 1.      ],
                            fixed_consts_units = [ [0,0,0] ],
                            free_consts_names = [ "m"       , "g"        ],
                            free_consts_units = [ [0, 0, 1] , [1, -2, 0] ],
                            op_names = ["mul", "add", "sub", "div", "inv", "n2", "sqrt", "neg", "exp", "log", "sin", "cos"]
)

SR task started...

100%|██████████| 1000/1000 [00:00<00:00, 99707.70it/s]
100%|██████████| 1000/1000 [00:00<00:00, 121658.66it/s]

=========== Epoch 00000 ===========
-> Time 135.42 s

Overall best  at R=0.537882
-> Raw expression : 
       2
c₀₀⋅x₀₁ 

Best of epoch at R=0.537882
-> Raw expression : 
       2
c₀₀⋅x₀₁

100%|██████████| 1000/1000 [00:00<00:00, 2729.74it/s]
100%|██████████| 1000/1000 [00:00<00:00, 66274.34it/s]

=========== Epoch 00001 ===========
-> Time 84.00 s

Overall best  at R=0.537882
-> Raw expression : 
       2
c₀₀⋅x₀₁ 

Best of epoch at R=0.537882
-> Raw expression : 
              1                     
────────────────────────────── + 1.0
   cos(1.0)      2                  
- ℯ         - 1.0  - 1.0 + 1.0      
────────────────────────────────────
             ⎛   1    ⎞             
             ⎜────────⎟             
             ⎜⎛ c₀₀  ⎞⎟             
             ⎜⎜──────⎟⎟             
             ⎜⎜     2⎟⎟             
             ⎜⎜⎛ 1 ⎞ ⎟⎟             
             ⎜⎜⎜───⎟ ⎟⎟             
             ⎝⎝⎝x₀₁⎠ ⎠⎠

100%|██████████| 1000/1000 [00:00<00:00, 3519.95it/s]
100%|██████████| 1000/1000 [00:00<00:00, 38586.05it/s]

=========== Epoch 00002 ===========
-> Time 27.64 s

Overall best  at R=0.537882
-> Raw expression : 
       2
c₀₀⋅x₀₁ 

Best of epoch at R=0.537882
-> Raw expression : 
            ⎛                     0.5⎞
            ⎜⎛          0.5      ⎞   ⎟
            ⎜⎜⎛   ⎛1.0⎞⎞         ⎟   ⎟
            ⎜⎜⎜log⎜───⎟⎟         ⎟   ⎟
       2    ⎜⎜⎜   ⎝1.0⎠⎟         ⎟   ⎟
c₀₀⋅x₀₁ ⋅sin⎜⎜⎜────────⎟    + 1.0⎟   ⎟
            ⎜⎜⎜   1.0  ⎟         ⎟   ⎟
            ⎝⎝⎝  ℯ     ⎠         ⎠   ⎠

100%|██████████| 1000/1000 [00:00<00:00, 3211.26it/s]
100%|██████████| 1000/1000 [00:00<00:00, 77247.44it/s]

=========== Epoch 00003 ===========
-> Time 27.45 s

Overall best  at R=0.577732
-> Raw expression : 
      c₀₀⋅c₀₁       
────────────────────
       1          1 
- ──────────── + ───
  -3⋅x₀₀ + x₀₀   x₀₀

Best of epoch at R=0.577732
-> Raw expression : 
      c₀₀⋅c₀₁       
────────────────────
       1          1 
- ──────────── + ───
  -3⋅x₀₀ + x₀₀   x₀₀

100%|██████████| 1000/1000 [00:00<00:00, 14587.11it/s]
100%|██████████| 1000/1000 [00:00<00:00, 106292.55it/s]


print(expression.get_infix_pretty(do_simplify=True))
print(expression.get_infix_latex(do_simplify=True))
print(expression.free_const_values.cpu().detach().numpy())

pareto_front_complexities, pareto_front_expressions, pareto_front_r, pareto_front_rmse = logs.get_pareto_front()
for i, prog in enumerate(pareto_front_expressions):
    # Showing expression
    print(prog.get_infix_pretty(do_simplify=True))
    # Showing free constant
    free_consts = prog.free_const_values.detach().cpu().numpy()
    for j in range (len(free_consts)):
        print("%s = %f"%(prog.library.free_const_names[j], free_consts[j]))
    # Showing RMSE
    print("RMSE = {:e}".format(pareto_front_rmse[i]))
    print("-------------")

                2     
             m⋅v      
g⋅m⋅z + ──────────────
                     2
        (-1 + cos(1)) 
g m z + \frac{m v^{2}}{\left(-1 + \cos{\left(1 \right)}\right)^{2}}
[46.40785791  0.26077131]
   2
m⋅v 
g = 1.000000
m = 1.253876
RMSE = 6.915446e+01
-------------
136044688160947⋅g⋅m⋅z
─────────────────────
   100000000000000   
g = 2.999864
m = 2.999864
RMSE = 5.883228e+01
-------------
                2     
             m⋅v      
g⋅m⋅z + ──────────────
                     2
        (-1 + cos(1)) 
g = 46.407858
m = 0.260771
RMSE = 1.384834e-06
-------------
                2     
             m⋅v      
g⋅m⋅z + ──────────────
                     2
        (-1 + cos(1)) 
g = 46.407858
m = 0.260771
RMSE = 1.384834e-06
-------------